Interconnected Autonomous Science Labs Empowered by HPC and Intelligent Agents
Autonomous science is rapidly emerging as a transformative approach to accelerate discovery across domains such as materials science, energy, climate, and health. These advances are powered by the convergence of artificial intelligence (AI), robotics, high-performance computing (HPC), and intelligent automation. However, current autonomous laboratories often operate in isolation, lacking the ability to collaborate across institutions and infrastructures. This BoF session will convene stakeholders from science, computing, and automation communities to explore how we can connect autonomous capabilities into a cohesive and interoperable ecosystem.
Participants will examine the role of HPC in this new landscape, not only as a computational engine but also as a decision-support platform that enables near real-time coordination of scientific activities across multiple facilities. We will explore how intelligent agents can leverage HPC systems to synthesize data from distributed instruments, run predictive models, and adaptively refine experiments. These capabilities challenge traditional batch scheduling and require new approaches to co-scheduling, data federation, and policy coordination across diverse infrastructures. The session will also highlight the importance of trust, verification, and reproducibility in scientific investigations that are increasingly shaped by autonomous decisions.
Interactive discussions will engage participants in identifying community needs, infrastructure gaps, and research priorities. Attendees will collaborate on articulating technical, organizational, and policy challenges that currently limit the deployment of interconnected autonomous labs. These include the lack of standardized APIs for instrument control, the difficulty of maintaining provenance and FAIR compliance across institutions, and the absence of communication protocols that support scalable agent coordination.
The BoF will bring together researchers, facility operators, software developers, industry partners, and policy experts to share their experiences and aspirations for autonomous science. Industry plays a critical role in advancing autonomous laboratory capabilities through the development of instruments, automation platforms, and scalable software infrastructure. Their engagement is essential to drive standardization, ensure interoperability, and accelerate technology transfer into real-world scientific and commercial environments. By connecting efforts across national laboratories, universities, industry, and international initiatives, this session aims to catalyze new collaborations and advance a shared roadmap for integrating autonomous systems into the scientific enterprise.
